Abstract. Non-expert users have to accomplish non-trivial tasks in application and device-rich computing environments. The increasing complexity of such environments is detrimental to user productivity (and occasionally, sanity). We propose to reduce these difficulties by shifting focus to what users want to do (i.e., on the tasks at hand) rather than on the specific means for doing those tasks. We call this shift in focus "task computing"; we argue that "task computing" offers an incentive to device manufacturers to incorporate semantic web technologies into their devices in order to get the benefits of easier and more flexible use of their devices' features by end-users. To support task computing, we developed an environment called a "Task Computing Environment" (TCE), which we have implemented using standard Semantic Web (RDF, OWL, DAML-S), Web Services (SOAP, WSDL) and pervasive computing (UPnP) technologies, we describe and evaluate our TCE implementation, and we discuss how it has been used to realize various deviceusage scenarios.
Unreliable wireless links can cause frequent link (and route) failures, creating a major challenge for routing protocols who need to constantly repair routes and find alternate paths. In this paper we propose DADR (Distributed Autonomous Depth-first Routing), a new distributed distance-vector routing protocol designed to adapt quickly to changing link conditions while minimizing network control overhead. In our algorithm, when a link fails, data packets are rerouted through an alternate next hop, and the information about the failed link is propagated with the data packet; therefore, routes are updated dynamically and with little overhead. We have implemented DADR on several link-layer technologies and deployed it in different applications, including AMI deployments in Japan [1]; all implementations resulted in reliable networks that were easy to set up, maintain, and resilient to changing conditions.
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